class_docstr: Evaluator for targeted molecule discovery task. Metric is the mean, optimum, and good percentage of property scores among generated molecular geometries.
  
  Args:
      prop_name (str): A string indicating the name of the molecular property, use 'gap' for HOMO-LUMO gap or 'alpha' for 
          isotropic polarizability. (default: :obj:`gap`)
      good_threshold (float): The threshold used to identifying whether a property score is good or not. Use 4.5 for HOMO-LUMO gap, and lower than 4.5 is considered
          as good. Use 91 for isotropic polarizability, and higher than 91 is considered as good.
code: def __init__(self, prop_name="gap", good_threshold=4.5):
      assert prop_name in ["gap", "alpha"]
      self.prop_name = prop_name
      self.good_threshold = good_threshold
  
file_path: DIG/dig/ggraph3D/evaluation/metric.py
imports: import torch
  import numpy
  from dig.ggraph3D.utils import xyz2mol, collect_bond_dists, compute_mmd, compute_prop
label_desc: Use image node_id 1 to create a new PropOptEvaluator object  with example: obj = PropOptEvaluator(prop_name, good_threshold)